Flow Rate Estimation Research Articles

A Heuristic Observer Design for an Uncertain Hyperbolic PDE using Distributed Sensing

We design an adaptive observer for semi-linear 2 × 2 hyperbolic PDEs with parametric uncertainties in both state equations. The proposed method is an extension of a previous result where parametric uncertainties were only allowed in one of the system equation. We utilize partial state measurements of one of the distributed states to estimate the remaining unknown distributed state. The method can be applied to flow rate estimation in fluid flow systems where the pressure is measured.

Hydrological modelling in small ungauged catchments.

The knowledge of the frequency and magnitude of low flow events is necessary to mitigate social, economic and ecological impacts inside the basin. However, the measurement network in Brazil is still restricted to large drainage areas, while basins with less than 300 km2 remain ungauged. Among different flow estimation methods, we used a rainfall-runoff model designed specifically to estimate flow rates during the dry season in small ungauged basins: the Silveira Method (SM). We tested the model performance for the São Bartolomeu river basin (Minas Gerais, Brazil), a small ungauged basin that experienced severe droughts and water supply shortages in 2014-2016. We tested eleven different scenarios based on the time and duration of drought periods used to estimate the model parameters. In the best scenario, the model underestimated low flow rates by 31% for Q95 and was considered suitable to predict local low flow. Finally, the model results suggest that a water volume higher than the river can support has been granted concession during the dry season, which may lead to an unsustainable water supply scenario soon. This result showed the capacity of SM as a complementary tool for the evaluation of water potential in small basins.

Evaluation of hole-specific injection rate based on momentum flux measurement in GDI systems

A novel methodology for the estimation of the mass flow rate delivered by each hole of a multi-hole GDI nozzle is presented and discussed in this paper. The proposed method is based on the measurement of the impact force of each jet and it is able to evaluate the individual hole injection rate and injected mass using the relationship between the spray momentum flux and the mass flow rate. Three different nozzles are tested, one featuring equal hole diameters and two with differentiated hole-to-hole dimensions. Firstly, results are validated in terms of total injection rate, comparing the sum of the individual hole flow rates with the signal from a Zeuch-based flow meter. Secondly, outcomes are compared with the direct measurement of the injected quantity by means of a special device able to collect and weight the fuel delivered from each hole.Results evidence an excellent agreement in terms of mass flow rate dynamic profile as the proposed method is able to detect both opening and closure transients and the static flow rate. The proposed method proved to be able to capture the dynamic mass flow rate in transient conditions, i.e. very short injections, overcoming a limitation of the methodology proposed in a previous study. Moreover, in terms of injected mass, the results show a percentage error lower than 5% for medium and long energizing times and a maximum error of 9.5% for short injections in ballistic operating conditions.

Detection and estimation of valve leakage losses in reciprocating compressor using acoustic emission technique

Valve problems in reciprocating compressor are often resolved through parameter analysis of acoustic emission (AE) signals or intelligent system without examining the nature of signals related to its source. This study intended to explore the potential of AE signal for the measurement of valve flow rate in order to quantify the severity of valve problems. The study started with time-frequency analysis of AE signal through discrete wavelet transform, followed by valve condition classification and valve flow rate estimation for faulty valves operated from 450 to 750 rpm. The k-nearest neighbours (KNN) and support vector machine (SVM) classification algorithms are employed to classify the valve conditions before estimation of valve flow rate through regression model. The prediction accuracy of valve flow models is found between 74.5 and 98.8%. Finally, the valve leakage loss can be estimated by computing the difference of flow rate between the measured valve and its baseline (normal valve) using AE parameter.

Volume Flow Rate Estimation for Small Explosions at Mt. Etna, Italy, From Acoustic Waveform Inversion

AbstractRapid assessment of the volume and the rate at which gas and pyroclasts are injected into the atmosphere during volcanic explosions is key to effective eruption hazard mitigation. Here, we use data from a dense infrasound network deployed in 2017 on Mt. Etna, Italy, to estimate eruptive volume flow rates (VFRs) during small gas‐and‐ash explosions. We use a finite‐difference time‐domain approximation to compute the acoustic Green's functions and perform a full waveform inversion for a multipole source, combining monopole and horizontal dipole terms. The inversion produces realistic estimates of VFR, on the order of 4 × 104 m3/s and well‐defined patterns of source directivity. This is the first application of acoustic waveform inversion at Mt. Etna. Our results demonstrate that acoustic waveform inversion is a mature and robust tool for assessment of source parameters and holds potential as a tool to provide rapid estimates of VFR in near real time.

Improved Real–Time Estimation of Return Flow Rate of Drilling Fluids by Model Adaptation for Friction Parameter

Early kick and loss detection is a major concern in any drilling operation. A real-time return flow rate measurement would be an added advantage for the early kick and loss detection for conventional drilling systems. In this paper, the real-time estimation of the return flow rate during drilling is studied, using a Venturi channel. A reduced order, 1D, mathematical equation for the shallow water flow/open flow in the Venturi channel is investigated with various non-Newtonian friction models. The volumetric fluid flow rate is estimated online using an unscented Kalman filter. In order to improve the fluid flow rate estimation, the model is adapted to some of the rheological parameters in real time. A simple and effective fit–for–purpose friction model is developed and compared with the other friction models from literature. The fit–for–purpose model has the least estimation error (RMSE 1.465%) and requires less information as inputs. The proposed method exhibits promising potential to be used as an online return flow rate measurement for early kick and loss detection in conventional drilling.

Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks

Comparison of Two-Phase Critical Flow Models for Estimation of Leak Flow Rate through Cracks

Estimation of Flow Rate and Thermohaline Characteristics of Atlantic Water in the Eurasian Basin

The large set of CTD data obtained within the NABOS program in 2002–2008 is analyzed. The description of variability of θ, S-indices, and flow rate of the geostrophic current transporting Atlantic water along the continental slope of the Eurasian Basin is presented. It is shown that the dramatic warming of Atlantic water registered in 2006 was accompanied by an increase in the flow rate of the geostrophic currents throughout its path in the Eurasian Basin up to 142° E. The current characteristics derived from CTD data are given. The variability of hydrological parameters characterizing the Atlantic water flow in the Eurasian Basin is interpreted. The results are important reference data and can also be used for the comparative assessment of the amplitudes of variability of 9 and S-indices arising from climate change in the Arctic Basin.

Experimental and numerical investigation for the geometrical parameters effect on the labyrinth-seal flow characteristics of fast reactor fuel assembly

The labyrinth seal is widely used in the fast reactor fuel assembly to control leakage flow rate, adjust pressure drop and cool assembly outer wall. In the current investigation, a new non-rotating labyrinth seal with right-angle trapezoidal throttle tooth is designed and manufactured, and its flow characteristics are experimentally and numerically investigated. Reynolds number from 61,512 to 81,261 is considered and experiment data were generated from hydraulic experiment conducted at constant water temperature (84 °C) in the labyrinth-seal test section. Numerical results with different turbulence model, wall-normal grid spacing, inlet turbulence intensity and stream-wise grid length are compared with experiment results to demonstrate the effectiveness of numerical simulation. Geometrical parameters have a significant effect on labyrinth-seal flow characteristics. Increasing throttle-tooth number, spacing and throttle-tooth thickness can improve the labyrinth-seal sealing performance, while increasing gap width influences the flow velocity limitation and increases the leakage. Labyrinth-seal resistance coefficient is validated to be independent of Reynolds number (61,512–81,261). It is deduced that the fully rough regime still exists in an annular-tube turbulence flow with high wall roughness. The energy dissipation caused by throttling effect, jet, vortex and secondary transverse turbulence is the main sealing mechanism. Moreover, a leakage-coefficient empirical correlation is obtained by regression analysis of experiment data, which can be used for the structure design of sodium-cooled fast reactor and preliminary estimation of leakage flow rate in similar non-rotating seals.

A three-dimensional algorithm for estimating water-tightness of cement-treated ground with geometric imperfections

Jet-grouted cut-off walls (JGCOWs) and jet-grouted earth-plugs (JGEPs) are commonly used as artificial water barriers to impede ground water from seeping downstream of dams or into deep excavation pits. However, due to positioning errors and variability of column diameters, seepage passages may occasionally penetrate through the water barrier, thus undermining its water-tightness. A three-dimensional discretized algorithm (TDA) is proposed for quantitatively estimating the effect of the above geometrical imperfections on the water-tightness. With given random geometries of the treated ground, this algorithm is able to examine whether a water barrier is penetrated by seepage passages. It further quantitatively estimates the flow rate through the water barrier with the given random geometry. When compared with the results from 3-D random finite element analysis, it was found that the TDA results show strong correlations with FEM results, but at a remarkably reduced computational cost. The TDA generally gives a slightly more conservative estimation of flow rate than the FEM counterpart due to the lengthened seepage distance due to random corrugations in the penetrating untreated zones.

Three‐Dimensional Acoustic Multipole Waveform Inversion at Yasur Volcano, Vanuatu

AbstractAcoustic waveform inversions can provide estimates of volume flow rate and erupted mass, enhancing the ability to estimate volcanic emissions. Previous studies have generally assumed a simple acoustic source (monopole); however, more complex and accurate source reconstructions are possible with a combination of equivalent sources (multipole). We deployed a high‐density acoustic network around Yasur volcano, Vanuatu, including acoustic sensors on a tethered aerostat that was moved every ∼15–60 min. Using this unique data set we invert for the acoustic multipole source mechanism using a grid search approach for 80 events to examine volume flow rates and dipole strengths. Our method utilizes finite‐difference time‐domain modeling to obtain the full 3‐D Green's functions that account for topography. Inversion results are compared using a monopole‐only, multipole (monopole and dipole), simulations that do not include topography, and those that use a subset of sensors. We find that the monopole source is a good approximation when topography is considered. However, initial compression amplitude is not fully captured by a monopole source so source directionality cannot be ruled out. The monopole solution is stable regardless of whether a monopole‐only or multipole inversion is performed. Inversions for the dipole components produce estimates consistent with observed source directionality, though these inversions are somewhat unstable given station configurations of typical deployments. Our results suggest that infrasound waveform inversion shows promise for realistic quantitative source estimates, but additional work is necessary to fully explore inversion stability, uncertainty, and robustness.

Multimodal imaging of multiphase flows with electromagnetic flow tomography and electrical tomography

In many fields of process industry, it is essential to be able to accurately measure the volumetric flow rates and mass flows of different materials flowing in the process pipes. To estimate the volumetric flow rate of a certain phase, the volumetric fraction and the flow velocity field of the phase in a cross-section of the process pipe need to be known. Electrical tomography (ET), such as electrical resistance tomography, can be used to measure the cross-sectional volumetric fractions in two-phase flows. For velocity field metering, electromagnetic flow tomography (EMFT) techniques have recently been developed. By combining the multimodal information from the ET and EMFT modalities, volumetric flow rates in process pipes can be estimated. This paper reports the results from experiments applying a multimodal imaging approach utilizing an earlier developed EMFT system and a commercial ET system, combined for measuring the volumetric flow rates in a laboratory flow loop. The studies undertaken in the paper demonstrate that the proposed multimodal imaging approach can produce reliable volumetric flow rate and mass flow rate estimates in laboratory environment in the cases of oil–water and solids–water flows. The relative errors of the estimated volumetric flow rates in the case of oil–water flows, with the average flow velocity between 0.79 ms−1 and 1.17 ms−1, were found to be in the range of 7.8%–9.5%, the average being 8.2%.

Aliskiren, Fosinopril, and Their Outcome on Renin-Angiotensin-Aldosterone System (RAAS) in Rats with Thyroid Dysfunction.

Background and Objectives Thyroid hormones have an important role in the growth and development of various tissues including the kidney, which is the major site of renin release and the consequent angiotensin and aldosterone formation. Therefore any derangement in thyroid function can result in abnormal functioning in the renin-angiotensin-aldosterone system. The current study was undertaken to find the impact of using a direct renin inhibitor (Aliskiren) and an angiotensin-converting enzyme inhibitor (Fosinopril) on the components of the renin-angiotensin-aldosterone system (RAAS) in rats with thyroid dysfunctions. Method Forty-two male albino rats were divided into three subgroups. First group (6 rats) served as control. Second group (18 rats) served as hyperthyroid group (6 rats positive control, 6 rats given Aliskiren, and 6 rats given Fosinopril). Third group (18 rats) served as hypothyroid group (6 rats positive control, 6 rats given Aliskiren, and 6 rats given Fosinopril). Induction of hyperthyroidism and hypothyroidism was done through daily oral administration of L-Thyroxine and Propylthiouracil, respectively. On day 40 of the study, the rats were sacrificed and blood was collected for estimation of renin, angiotensin I, angiotensin II, aldosterone, TSH, T3, and T4. The collected blood samples were also used for estimation of levels blood urea, serum creatinine, liver enzymes, and serum electrolytes. Blood pressure and urine collection were done on days 1 and 40. The collected urine was used for estimation of urine flow, sodium excretion, and potassium excretion rates. Results In hypothyroid induced rats, serum renin level dropped as expected, while the use of Aliskiren and Fosinopril on these hypothyroid rats raised renin level due to the feedback mechanism. Both angiotensin I and II were significantly (P <0.05) lower than normal levels in the hypothyroid rats, unlike the level of aldosterone, which was higher than normal level. There was nonsignificant lowering in BP (systolic, diastolic, and mean BP) in the hypothyroid rats. Treatment of these rats with Aliskiren and Fosinopril did not lower the blood pressure more than normal when compared to the hypothyroid group. The hypothyroid rats also showed a decrease in level of serum creatinine. In hyperthyroid rats, there was a rise in levels of serum renin, angiotensin II, and aldosterone; nevertheless, the increase in angiotensin I level was significant. The use of Aliskiren and Fosinopril increased the level of renin nonsignificantly (decreased angiotensin I significantly). Hyperthyroid rats showed a significant increase in systolic, diastolic, and mean blood pressure. Both Aliskiren and Fosinopril increased urine flow, Na+ excretion, and K+ excretion rates. Aliskiren was better at reducing the high blood pressure. Conclusion Aliskiren and Fosinopril in hyperthyroid rats decreased serum angiotensin I, angiotensin II, and aldosterone. Blockade of renin and inhibition of angiotensin-converting enzyme both resulted in a rebound increase in level of renin in hypothyroid rats. Aliskiren is better at controlling blood pressure in hyperthyroid rats. Urine flow, sodium excretion, and potassium excretion rates were improved by the use of Aliskiren and Fosinopril in hyperthyroid rats.

Quasi-Saturated Layer: Implications for Estimating Recharge and Groundwater Modeling.

This study presents an extension of the concept of “quasi‐saturation” to a quasi‐saturated layer, defined as the uppermost dynamic portion of the saturated zone subject to water table fluctuations. Entrapped air here may cause substantial reductions in the hydraulic conductivity (K) and fillable pore water. Air entrapment is caused by a rising water table, usually as a result of groundwater recharge. The most significant effects of entrapped air are recharge overestimation based on methods that use specific yield (S y), such as the water table fluctuation method (WTF), and reductions in K values. These effects impact estimation of fluid flow velocities and contaminant migration rates in groundwater. In order to quantify actual groundwater recharge rates and the effects of entrapped air, numerical simulations with the FEFLOW (Version 7.0) groundwater flow model were carried out using a quasi‐saturated layer for a pilot area in Rio Claro, Brazil. The calculated recharge rate represented 16% of the average precipitation over an 8‐year period, approximately half of estimates using the WTF method. Air entrapment amounted to a fillable porosity of 0.07, significant lower that the value of 0.17 obtained experimentally for S y. Numerical results showed that the entrapped air volume in the quasi‐saturated layer can be very significant (0.58 of the air fraction) and hence can significantly affect estimates of groundwater recharge and groundwater flow rates near the water table.

Aerosol Plume Characterization From Multitemporal Hyperspectral Analysis

In this paper, we focus on airborne hyperspectral imaging methodology to characterize particulate matter (PM) near industrial emission sources. Two short-term intensive campaigns were carried out in the vicinity of a refinery in the south of France, in September 2015 and February 2016. Different protocols of in situ PM measurements were performed, at stack measurements (flow rate and offline chemical analysis) and online measurement at the refinery border (size distribution, concentration, and chemistry of aerosols). A multitemporal methodology to retrieve aerosol type, to map the aerosol concentration, and to quantify mass flow rate from airborne hyperspectral data is described in this paper. This method applied to the refinery detected plume from the main stack yields a black carbon to sulfate ratio of 10/90 in mass inside the plume, with an average size distribution smaller than 100 nm. These results are in a good agreement with the online analysis of aerosols at the refinery border. The resulting quantitative map with a metric spatial resolution leads to an estimated flow rate of about 1 g/s and is in a good agreement with in situ stack measurements and modeling.

Novel forecasting models for immediate-short-term to long-term influent flow prediction by combining ANFIS and grey wolf optimization

Accurate influent flow forecasting plays a significant role in management, operation, scheduling and utilization of the sewage treatment plants. In design and operate such plants, it is essential to measure and forecast the influent flow rate in wastewater plants. In this paper, the Very immediate-short-term to long-term influent flow rate are modeled and forecasted by a new developed hybrid model of ANFIS and Grey Wolf Optimizer (GWO). The objective of this study is the integration of GWO with ANFIS in forecasting multi-ahead influent flow rate. The forecast horizon of the model is from 5 min up to 10 days bases on Gamma Test (GT) feature selection of input combinations. As the parameters of ANFIS have effect on the forecasting accuracy, these parameters are adjusted and optimized by using Grey Wolf Optimizer (GWO). Then the choice of appropriate input parameters at different prediction horizons from Very immediate-short-term (5-min ahead) to long-term (10 days ahead) was discussed for influent forecasting. The statistical indices of RMSE, NSE, MAE, RAE, R2, d, CI and graphical evaluations such as scatter-plots with confidence bounds, error distributions, Taylor diagrams, box-plots and empirical cumulative distribution function (ECDF) were implemented for assessing the performance of all models in prediction horizons. Furthermore as another novelty in the present paper, recursive forecasting models based on previous forecasted values is used to improve the accuracy and applicability of ANFIS-GWO in recursive predictions. Our Results showed that: (1) the hybrid of ANFIS-GWO significantly improved the prediction accuracy. (2) ANFIS-GWO performs more efficiently than the ANFIS in almost all of the prediction horizons (ANFIS-GWO1: 5 min ahead; ANFIS-GWO11: 1–2 days ahead; ANFIS-GWO8: one week ahead). (3) The performance of models in influent flow forecasting is significantly influenced by the prediction horizon. The computational results confirmed that the ANFIS-GWO performs well in all of prediction horizons. Equally the true values and the trends are precisely forecasted by the ANFIS-GWO. Results of this novel study demonstrate that reliable estimates of influent flow rate from 5-min up to 10 days in advance can be achieved using the developed direct and recursive hybrid GWO models.

Development of an infrared seed-sensing system to estimate flow rates based on physical properties of seeds

Seed drills are usually used for sowing various seeds with different physical properties. It is important to develop a sensing system for planters capable of measuring the sowing rate of various kinds of seeds with the same settlement. For this purpose, an infrared sensing system was developed comprised of IR LEDs and photo-diodes on the opposite sides. When a seed stream passes, the output voltage of the light-receiving sensor changes proportionally in response to changing in the intensity of light at the receiving element. The voltage changes were added using a microcontroller and converted to an analog value by DAC chip. The test apparatus was designed to calibrate and evaluate the sensor with three types of seeds of chickpea, wheat, and alfalfa. These seeds respectively represent the large, medium and the fine seeds. The results revealed a good correlation between the voltage received from the seed sensor and the mass flow of seeds in the delivery tube. A model was developed for seed flow rate based on sensor output voltages, thousand seed weight and equivalent diameter of seeds. The coefficient of determination for the model was 0.94. So, it was concluded that the seed flow rate could be estimated based on some physical properties and output sensor voltage. The developed infrared sensing system could be used for the assessment of planter rows performance in the laboratory. It could provide an easy calibrating method for seed drills before planting in the field.

A review of methodological approaches for saturation flow estimation at signalized intersections

The estimation of the saturation flow is the utmost component for performance evaluation of a signalized intersection. The flow rate estimation procedure includes the analysis of the vehicles headway, vehicles discharge rate, passenger car unit, effective green time and cycle length of the signalling system. This study attempts to exhaustively review the existing literature and its suitability along with the multiple factors affecting the performance of signalized intersection. Different methodological approaches and soft computing techniques used worldwide by the researchers both in developed and developing countries are emphasized. This study also highlights the several influencing factors that have a significant impact on saturation flow value and several methodological approaches to determine the flow value through normalizing the influencing factors, which lead to a better way for planning and designing of a signalized intersection.

Identification, Characterization, and Prediction of Traffic Flow Patterns in Multi-Airport Systems

Efficient planning of airport capacity is key for the successful accomplishment of traffic flow management. Yet, the dynamic and uncertain behavior of capacity-determining factors makes it difficult to estimate flow rates precisely, especially for strategic planning horizons. Metroplex systems impose additional challenges in this decision-making process because of relevant operational interdependencies between the closely located airports. This paper presents a data-driven framework to identify, characterize, and predict traffic flow patterns in the terminal area of multi-airport systems toward improved capacity planning decision support in complex airspace. Through the identification and characterization of patterns in the terminal area traffic flows, we learn recurrent utilization patterns of runways and airspace as well as relevant decision factors, and use that knowledge to develop descriptive models for metroplex configuration prediction and capacity estimation. The framework is based on the application of machine learning methods on historical flight tracks, weather forecasts, and airport operational data. A multi-layer clustering analysis is first performed to mine spatial and temporal trends in flight trajectory data for identification of traffic flow patterns. Based on this knowledge, a multi-way classification model is developed to generate probabilistic forecasts of the metroplex traffic flow structure for look-ahead times of up to eight hours. Finally, an empirical approach for arrival capacity estimation is proposed based on historical flow pattern behavior. The observed variability in throughput and terminal area delay performance emphasizes the importance of metroplex configuration predictability toward improved flow rate planning and ultimately better traffic regulation.

Impacts of land-use change on southeast Amazonia basin streamflow

The Amazon region is the subject of growing interest in the international scientific community due to the environmental services provided by its dense forests in climate regulation and freshwater. Despite many efforts from environmental management agencies and research centers, this region can still be considered poorly monitored, especially given its large regional and global importance. Rainfall-runoff models are presented as a good alternative to the estimated flow rates in inaccessible or difficult to watch places. This study simulated stream flows for a representative part of the Amazon basin using the Soil and Water Assessment Tool (SWAT) redistributed hydrological model, adopting as reference the streamflow observed in Altamira gauge station. The authors emphasize that a database was specially prepared with physical parameters such as land use, topography and soil types, and weather data encompassing the years from 1985 to 2012, at a daily time step. The chosen approach allowed carrying out hydrologic simulations that were consistent with the flow values observed at the Altamira gauge station, providing better understanding of hydraulic-hydrological processes in the Xingu subbasin and information for planning and decision-making on the management of water resources in this important river basin.